APPLICATION OF THE K-MEANS CLUSTERING METHOD FOR PERFORMANCE ASSESSMENT BASED ON EDUCATOR COMPETENCE

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Paul Erikson
Bobby Rahman Angkat
Eliza Christovel Yosua
Mutiara Sembiring
Marlince Nababan

Abstract

Performance appraisal is one thing to respect someone while working in an institution, one of which is a private higher education institution. To respect the performance of resources, there needs to be a value assigned to someone. Assessments carried out for one semester need to be reviewed again because during filling in the student assessments do not fill in according to their understanding so that a review needs to be carried out again. The assessment was carried out using the K-Means method by applying the concept of the centroid value. There are 4 (four) variables used, namely pedagogic competence, personal competence, social and professional competence with a value of K = 3. The maximum number of observations for cluster 3 is 368 while the value of Distances Between Cluster Centroids shows 2 suitable clusters, namely cluster 1 and cluster 2, which is 1.7020. The author gives suggestions to remove outlier data before entering the data to be trained into the algorithm to improve visualization if the dataset is large.


Key Word: Performance Appraisal, Data Mining, K-Means

Article Details

How to Cite
[1]
P. Erikson, B. R. Angkat, E. C. Yosua, M. Sembiring, and M. Nababan, “APPLICATION OF THE K-MEANS CLUSTERING METHOD FOR PERFORMANCE ASSESSMENT BASED ON EDUCATOR COMPETENCE”, JUSIKOM PRIMA, vol. 7, no. 1, pp. 250-254, Aug. 2023.
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